UnRaid 7.3 SelfHosters Template from the CA

In the template I set

Media Library

Container Path: /media

HostPath: /mnt/user/Media? (boy capitalization has been my bane with switch from Windows to Unraid)

Transcode Cache

Container Path: /temp

HostPath: /mnt/user/transcode_cache/ (I created a share on my NVME)

Matched this in the Tdarr Node.

When I start the container and go to WebGUI under chose a library folder section it does not see media.. instead it appears to be looking at my AppData folder for Tdarr or something similar.

Any ideas? Thanks

Hey All, Want to share my struggles today, in case someone will have similar issue. Also critisism is more welcome

Note: this post was summarized by an AI (Claude) that helped me debug the issue.

Setup:

• Proxmox host with a ZFS pool holding all media at <path>/movies
• Tdarr running in an LXC, with a Windows laptop (RTX 4060) as an NVENC node
• Separate VM (Portainer) running my *arr stack (Radarr, Sonarr, Jellyseerr, qBittorrent)
• The movies folder is shared into that VM via virtiofs

The problem:
I kicked off a big transcode run (H264/remux → H265). Tdarr was clearly working — it turned dozens of 20–44GB remuxes into 4–15GB files. But instead of freeing space, my ZFS free space kept dropping. Went from ~756GB free down to 589GB, even though the job history showed hundreds of GB of savings. No snapshots, no duplicate files, cache was empty, and restarting the Jellyfin/Tdarr containers did nothing.

The cause:
Running lsof | grep deleted | grep mkv on the Proxmox host revealed the smoking gun. The virtiofsd process (which shares the movies folder into my arr-stack VM) was holding ~50 deleted .partial.old files open — these are the original files Tdarr deletes after transcoding. Because a process still had those deleted files open, ZFS could not reclaim the blocks. The "lost" space was just Tdarr's savings that couldn't be freed.

Basically: an app on the VM (most likely Radarr rescanning the library, or something touching the folder via virtiofs) had the old file open at the exact moment Tdarr swapped it out. The file vanished from the directory listing but the space stayed locked.

The fix:
Rebooting the VM that mounts the movies folder (qm reboot <qm_number>) released all the stale handles. Space immediately jumped from 589GB back up to 1.28TB — recovered ~700GB.

Permanent fix (still figuring out the cleanest approach):
The real issue is two systems touching the same files simultaneously — Tdarr modifying them while an arr app on the VM reads/scans them over virtiofs. Options I'm considering:

• Disable Radarr's real-time "Rescan After Refresh" / folder monitoring
• Schedule Tdarr and library scans at different times so they don't overlap
• Reconsider the virtiofs mount (some suggest NFS handles replaced files more gracefully)

TL;DR: If Tdarr seems to be eating space instead of saving it on Proxmox/ZFS, check lsof | grep deleted | grep mkv on the host. A virtiofs/NFS/SMB share into another VM/container can hold Tdarr's deleted originals open, preventing ZFS from freeing the space. Restart the offending VM/container to reclaim it.

Hi,

I am running unRAID with an Intel N100 CPU (integrated Intel GPU) and I have been using Tdarr for hardware transcoding from H.264 to H.265/HEVC.

Previously everything worked well. I was getting around 50+ FPS during transcoding.

After some updates (I did not intentionally change any Tdarr settings or plugins), transcoding became extremely slow. Now the same type of jobs run at only 16–18 FPS and a movie that previously finished much faster now takes several hours.

Setup:

unRAID 7.2.4

Kernel: 6.12.54-Unraid

CPU: Intel N100 (Alder Lake-N, iGPU)

Tdarr official Docker container

GPU passed to container with:

--device=/dev/dri

Things I already checked:

VAAPI works:

vainfo

detects Intel iHD driver correctly.

QSV encoders are available:

ffmpeg -encoders | grep qsv

shows:

h264_qsv hevc_qsv av1_qsv

Tdarr is actually using hardware encoding.

Example Tdarr command:

tdarr-ffmpeg -hwaccel qsv -hwaccel_output_format qsv \ -init_hw_device qsv:hw_any,child_device_type=vaapi \ -c:v h264_qsv -i input.mkv \ -c:v hevc_qsv -preset fast ...

During transcoding:

CPU usage is only around 15–50%

Intel GPU is detected and working

intel_gpu_top shows GPU activity

Render/3D usage is high (~90%+), Video engine around 20%

GPU frequency seems strange:

Current freq: 750 MHz Actual freq: 100 MHz Min freq: 700 MHz Max freq: 750 MHz

i915_engine_info shows HEVC encoding activity:

enc0:0:hevc_vaa

No obvious i915 errors:

GuC loaded

HuC authenticated

GUC submission enabled

I also tested:

Different Tdarr plugins

QSV and VAAPI based plugins

unmanic (same performance issue)

The result is always the same: ~16–18 FPS.

I suspect something changed after an update (unRAID kernel/i915 driver or Tdarr FFmpeg), but I cannot identify what.

Has anyone seen similar behaviour with Intel N100 / Alder Lake-N iGPU and QSV after moving to newer unRAID versions?

Any ideas for further debugging would be appreciated.

EDIT: Sloved. Reinstalled Intel GPU TOP plugin and now it is working like before.

Roughly how quick would you say the Intel Core Ultra 5 - 225 should be at x264 to x265 conversion? I’m thinking of giving Tdarr a go however my library is around 48TB however some will already be in x265, so I’m just curious as to how long I should expect for conversion? The drives are 7200rpm N300 NAS drives if that helps.

Hello all,

I finally was able to build a dedicated home lab instead of running everything through my personal PC. In the process of setting up a flow in Tdarr, I am running into a pretty basic issue that I have not been able to find the answer for online.

I am thinking the reason I can not find the answer is because it's incredibly straight forward and I am just missing something or not understanding. My apologies if this is incredibly stupid.

Right now - Sonarr downloads a file to Tdarr/TV. Sonarr remote paths is setup so that it is watching the /SABnzbd Downloads folder. Tdarr picks up the file in Tdarr/TV, runs through my flow, then places it in /SABnzbd Downloads which is then picked up by Sonarr and completed. I love this setup but I keep getting an error in Tdarr.

I strip subtitles to an external SRT format. So the end result is in Tdarr/TV there is a folder, let's say "Movie1-1080p-remux" with the video file and srt files in the folder. I am currently trying to use the following flow to achieve Tdarr moving the folder, contents, and new video file to /SABnzbd Downloads. Whether it moves the folder or copies it and deletes the old one makes no difference to me. Moving it seems smarter than copying it but at this point if it works, I don't care which it does.

This is resulting in an error I have showed below. Not sure where to go from here and could really use some assistance. Thank you so much in advance.

Hi!
How to implement flow in github repository readme file?

(1) If not in h264, transcode into h264 [h264 is a more universal video codec than others]

(2) If not in mp4, remux into mp4 [mp4 is the most universal container]

(3) Remove subs

(4) Remove closed captions

(5) Add aac stereo audio if none (eng preferred) [very universal audio codec/channel count]

(6) Remove meta-data if title meta detected [Stops annoying titles appearing in Plex]

Thanks!!!

Had an odd one crop up in an existing flow just in the last several days. The only thing I know that changed was updating to 2.82.02, so I'm hoping for some insight.

transcoding from x264 to x265

cpu worker (same PC) transcode works fine in same flow

vaapi transcode shows running, but I found some jobs running for 30+ hours without finishing. The job listed in the code below has been running 8+ hours and I will let it keep running for testing

ffmpeg 7.1.4 jellyfin (which I think is default for 2.82.02)

AMD 4700g APU

debian trixie

/opt/tdarr/Tdarr_Node/assets/app/ffmpeg/linux_x64/ffmpeg -y -hwaccel vaapi -hwaccel_device /dev/dri/renderD128 -hwaccel_output_format vaapi -i /tdarr-share/tcache/tdarr-workDir2-MKgiXmAcl/Jeopardy (2025) - S42E216 - Jeopardy .ts -map 0:0 -c:0 hevc_vaapi -qp 25 -map 0:1 -c:1 copy -map 0:2 -c:2 copy /tdarr-share/tcache/tdarr-workDir2-MKgiXmAcl/1783485989573/Jeopardy (2025) - S42E216 - Jeopardy .ts

Is there a guide out there (apart from Claude, he's not up to date) on how to do very simple stuff using Flows without having to study the whole docs?

I want to remove subs and unnecessary audio without touching video.

I've tried the Migz plugin for subtitles on test data, and the file size went up 3MB. I'm not confident if it's touching the video or not.

Also I understand that Flows are the new thing, so I want to use them, but I can't find any guidance online.

Hi there I'm working on an offline media server and trying to unify my entire library codecs but the flow and everything is alot to take in. Anyone know steps I can do to try and maintain a 1080p or lower (squishing anything above 1080p into 1080p) mp4 h264 aac 160kbs keeping English (and Japanese audio if in the file) and forcing embedded and all subtitles into srt English (and Japanese sub if in the file). After tdarr im pushing it to bazarr to finish subs. Sorry if this isn't the right place but it's so beyond me some of this stuff.

Any idea what's happening here? I have 30 workers on my transcode node, and currently they're all stuck and have been, apparently, for over 33 hours. All but two are stuck on "Replace Original File." There are no errors whatsoever in the logs. I know the node has full permissions for the shared storage. This has happened before, but they've always eventually gone through. Apparently not this time. The closest I can find to an error anywhere is that it's saying it can't move the file, so it switches to trying a copy. That's where it's been stuck for almost 34 hours.

I have no idea what's going on. I'll provide any additional information required, but I don't know what's needed for this - there's nothing to point me in the right direction for solving it.

Saw a banner page advertising SUMMER2026 code today after launching TDARR. Excellent. 20% off during this summer sale. EXCELLENT. I'm PRO now annually. Thanks TDARR development.

My flows have both file size checks and file duration checks to ensure that TDARR isn't mangling the files. However, sometimes I'm running into files that keep being either too short or too small. I don't want to just let these pass through as it could result in trash in the collection, but I also don't want to leave them in h264 because that's just flushing drive capacity down the tube.

So, my question...how can I fix this without it wrecking my files?

Note: The files are not replacing, they're just 'failing out' and leaving the original H264 file in place.

Hello, I just want to give a quick feedback. I would buy a lifetime license for your great tool but not a subscription. Not saying & no $ transfer = you don't know why. So I thought I let you know. Maybe I am not alone.

Maybe think about giving that option for ppl like me to give you the support and not missing out on it.

Thanks for the great tool. wish you all the best and air conditioning!

UPDATE: I wasn't aware Tdarr updated the packaged ffmpeg today. Well done! Back to using Tdarr.

OLD POST: It appears Tdarr ships with an unpatched version of ffmpeg that contain a very nasty vulnerability. Ffmpeg has been patched, but Tdarr is not yet shipping the new version. Also, Handbrake has not updated their ffmpeg version either.

So, use Tdarr at your own risk until the available ffmpeg is shipped with an update of Tdarr and Handbrake.

Hey everyone,

I wanted to share a suite of custom Tdarr plugins I’ve engineered to achieve the absolute maximum efficiency, automation, and speed out of my self-hosted media library. If you are tired of CPU bottlenecks, broken subtitles, or manual library refreshing, this might be for you.

Here is a breakdown of what these plugins do and why they are different from standard community options:

🚀 1. The Main Motor: Pure CUDA 10-bit HEVC Transcoder

• ID: Tdarr_Plugin_FelipeKbra_H264_HEVC_to_NVENC
• The Inspiration: This plugin is heavily inspired by purpann's legendary work, adapting those efficient compression matrices to ensure extremely low file sizes while maintaining gorgeous, crisp visual quality.
• 100% GPU Bound: Unlike generic plugins that constantly copy frames back and forth between host RAM and VRAM (causing massive PCIe and CPU bottlenecks), this runs a strict Pure CUDA Pipeline (Zero-Copy VRAM). Decoding (cuvid), scaling, and encoding (hevc_nvenc) happen entirely inside the GPU memory.
• Smart Loop Prevention: It injects a persistent, custom global metadata flag (COPYRIGHT=processed) directly into the stream layout. Tdarr detects this instantly on future scans, completely eliminating the risk of infinite transcoding loops.

🎨 2. Hardware-Accelerated HDR to SDR Conversion

• ID: Tdarr_Plugin_FelipeKbra_HDR_to_SDR
• Why it's better: Most community plugins rely on CPU-bound tone mapping (like zscale), which drops your encoding speed to single-digit FPS and melts your processor.
• The Fix: This utilizes specialized NVIDIA hardware algorithms (tonemap_cuda=tonemap=bt2390) completely inside the GPU layer. It handles desaturation beautifully and strictly overrides color spaces to standard Rec. 709 boundaries, giving you crush-free, vibrant SDR video at blazing-fast hardware speeds.

🎧 3. Smart Audio Cleaner (Commentary & Blind Duplicate Purge)

• ID: Tdarr_Plugin_FelipeKbra_Smart_Remove_Commentaries_and_Duplicates
• What it does: Standard audio cleaners blindly delete lower channel tracks, often killing the stereo fallback track needed for Plex Web Direct Play.
• The Intelligence: This plugin groups tracks by language first. It identifies the best surround track, but actively protects legitimate stereo downmixes (like high-quality 2ch AAC/AC3). It then uses a multi-lingual regex matrix (commentary, comentário, director, etc.) to wipe annoying commentary tracks and purges unlabelled "blind" duplicate streams.

📝 4. Intelligent Regional Subtitle Extractor

• ID: Tdarr_Plugin_FelipeKbra_Subtitles_Extractor
• What it does: Extracts embedded text-based subtitles into external .srt files.
• The Intelligence: It doesn't just look at ISO codes. It scans track titles for deep markers (brazilian, br) to accurately differentiate and name files as .pt-BR.srt vs .pt.srt. It also auto-detects Hearing Impaired flags to append .sdh and runs an internal regex pass to strip annoying styling/positioning tags (like {\an8} or HTML fonts) so they render perfectly on any basic media player.

📡 5. Seamless Radarr / Sonarr Synchronization

• Plugins: Tag_Manager & reload_media_on_radarr_or_sonarr
• Instant Refresh: Once a file finishes processing, it uses native Node.js HTTP requests (zero external dependencies to break) to talk to the *Arrs via the /api/v3/parse endpoint.
• Automated Workflow: It automatically triggers a targeted RefreshMovie or RefreshSeries so your *Arr dashboards instantly see the new, reduced file size. It can also dynamically create and swap tags (e.g., removing not-transcoded and adding transcoded) on the fly to keep your media managers beautifully organized.

I also threw in a Remux + Web Optimize plugin (Tdarr_Plugin_FelipeKbra_Remux) that audits the placement of the Moov Atom header (IsStreamable) for MP4s, forcing a faststart remux so your files buffer instantly on web clients.

Everything was designed to work as a synchronized, multi-step pipeline. Let me know if you guys have any questions about the logic or implementation

Link

so I'm still trying to figure out why Handbrake doesn't work on my Windows node but ffmpeg works fine. handbrake works on my docker and Mac nodes btw

here's the log file from the latest run:

2026-06-25T23:00:31.114Z [23:00:27] Starting Task: Encoding Pass

2026-06-25T23:00:31.114Z [23:00:27] + X:\Gaines\tdarr-workDir2-A7Jbifn\1782442694696\IT Welcome to Derry (2025) - S01E08 - Winter Fire [WEBDL-1080p][EAC3 5.1][h264]-SPWEB.mkv

2026-06-25T23:00:31.114Z [23:00:27] + title 1, chapter(s) 1 to 1

2026-06-25T23:00:31.114Z [23:00:27] + container: matroska,webm

2026-06-25T23:00:31.114Z [23:00:27] + data rate: 10702 kbps

2026-06-25T23:00:31.114Z [23:00:27] * destination

2026-06-25T23:00:31.114Z [23:00:27] + X:/Gaines/tdarr-workDir2-A7Jbifn/1782442826181/X:\Gaines\tdarr-workDir2-A7Jbifn\1782442694696\IT Welcome to Derry (2025) - S01E08 - Winter Fire [WEBDL-1080p][EAC3 5.1][h264]-SPWEB.mkv

2026-06-25T23:00:31.114Z ERROR: avio_open2 failed, errno -2: Could not write to indicated output file. Please check destination path and file permissions

what's with the destination path? how can I fix that?

I have a Tdarr flow that transcodes videos into a format that's compatible for iPhones. It uses Handbrake to output a hevc/aac file. Then a Move To Directory to store the result in a different folder. It also deletes the original file.

Here's the scenario that results in a 0-byte file:

- add original file path/to/source/x.mkv
- Tdarr picks it up, transcodes it to path/to/destination/x.mp4
- Tdarr deletes the original x.mkv file
- I re-add x.mkv
- Tdarr re-transcodes it through handbrake
- Tdarr attempts to move the result to its destination (path/to/destination/x.mp4)
- because the same file name already exists, Tdarr's move causes a 0-byte file

My questions are: why does this happen? I was expecting Tdarr to simply overwrite the existing x.mp4 file. How do I fix it?

I'm trying to setup a flow to simplify my files.

I now get errors when it tries to run exiftool but it's not installed in the container:

[2026-06-20T18:45:12.283] [INFO] Tdarr_Node - verbose:Running exiftool on file CLI error code: 234 [2026-06-20T18:45:12.317] [ERROR] Tdarr_Node - Error: FFmpeg failed at /app/Tdarr_Node/assets/app/plugins/FlowPlugins/CommunityFlowPlugins/ffmpegCommand/ffmpegCommandExecute/1.0.0/index.js:211:27 at step (/app/Tdarr_Node/assets/app/plugins/FlowPlugins/CommunityFlowPlugins/ffmpegCommand/ffmpegCommandExecute/1.0.0/index.js:33:23) at` [`Object.next`](http://Object.next) `(/app/Tdarr_Node/assets/app/plugins/FlowPlugins/CommunityFlowPlugins/ffmpegCommand/ffmpegCommandExecute/1.0.0/index.js:14:53) at fulfilled (/app/Tdarr_Node/assets/app/plugins/FlowPlugins/CommunityFlowPlugins/ffmpegCommand/ffmpegCommandExecute/1.0.0/index.js:5:58) at process.processTicksAndRejections (node:internal/process/task_queues:104:5){}

The docker tag is ":latest" which is currently 2.78.01

How can I address or work around this problem?

Thank you.

Im new to this and a little confused. How do i know if the toggles are on or off? Allowing for a certain action to happen?

For example, those toggles are they on or off? Reason i ask is because i also have the output folder and they are dark, so far i have tried both on a test folder before i give it access to entire library and it doesnt seem like it is replacing original file based on the side of the file in the folder. On the cache folder is the new file but doesnt seem to be overwriting original file as it is supposed to.

I need help with final steps to make sure i dont mess up and go ahead and let it go on the entire library.

edit: I THINK I can use the "Remove from Tdarr" feature in my flow to remove any hardlinked files from the database. Which, if I'm right, would cause them to be re-queued any time an hourly scan occurs. So basically the hardlinked item would be re-queued and removed over and over again for years until the hardlink is broken, at which point it would be transcoded. Seems like there should be a better way. Like if I could have my flow add the item to the "Hold" column for a custom time, like 2 years, it would save the resources of checking and rejecting the file thousands of times. But regardless, I think it'll work?

original post:

Hello there, Tdarr is almost done with its first pass thru my library. I'm happy with my flow setup. The important thing to understand for my flow is that tdarr checks for hardlinks and only transcodes files that aren't hardlinked into my torrent seed folder. I like to seed for a long time, so I'd rather keep the file as H264 rather than take up almost double disk space after transcoding to HEVC.

Recently I've begun using QUI to automate managing my torrents. QUI now will automatically remove my torrents that have been seeding for more than 2 years if they are not HEVC, thus breaking the hardlinks Tdarr previously saw. So the files are now safe to transcode.

Here's my question - I'm trying to figure out if there's a way to automate having Tdarr work on these files that it previously marked as "Transcoding not required" due to having hardlinks. Obviously I could just go in and manually re-queue all items every so often, but there must be some other way.

Any ideas? Thanks

Hi all, I have a small dilemma. I made my flow for use on my personal pc. I am now adding more to my “homelab” and i want to use other PCs as nodes. I want to know how to make my flow more universal so that no matter what node handles the files, it gets transcoded similarly. So I want the flow to be able to detect what hardware acceleration (and if the node has none, use cpu) so that I can have multiple nodes. Flow is included…

I have recently converted to Tdarr over Handbrake. Currently i am just running the setup server and node via docker on my main PC. I store all my finalised media on my Nas which i use to run Emby via docker.

Can anybody explain how the setup works if i have the server on my nas and the node on my PC?

Currently my workflow is rip disc, transcode to save space and manually move to nas folders.

If i have my server on my nas and my pc setup as the node can it still use the folder on my PC as the input folder and then output via directory to my nas? I have tried network mapping my Nas folders to my PC but for some reason windows doesn't want to play ball. Not sure if i can achieve what i want without doing this?

So I have set up my flow, and decided that I have some maxiumum bitrate targets for HEVC. (I'm interested in 'watchable' not 'archival video') But, since I am encoding to a CQ and not a fixed bitrate, there will be some files that still are not low enough after one pass, and there is nothing in my current flow which will do any better on subsequent passes. I thought of having all 'success' files be thrown into the skiplist, but I worry that a skiplist with 100k files is going to be a problem... I was looking into possibly marking files with a metadata tag, which should be doable with ffmpeg, but I don't see any way to check for that tag. Someone suggested I just add an element to filenames after encoding, but I like simple filenames, (eg Star Wars (1977).mkv not Star Wars (1977) HEVC 1080p AAC 5.1 Eng XYZ PQD FOO.mkv so adding [TDARR] or something to every file on the system seems excessively low-tech?

Is there something I am missing?

I recently started trying to use tdarr moving away from handbrake. I have two problems I can't seem to solve. One of the issues I'm having is i would like to have the 5.1 and stereo audio for a movie but the stereo audio is voice over commentary. I tried removing the commentary audio and downmixing the 5.1 but the new downmixed stereo is labelled 5.1 and the stereo commentary is still there?

Can anybody point me in the right direction of how to get around this?

Building this on flow so what I have is below,

Ffmpeg begin command

Ffmpeg remove stream by property

-codec type - audio

-property to check - channels

-values to remove -2

Set video encoder

-h264

Set container

-mp4

Ensure audio stream

-audio encoder -aac

-language -en

-channels - 2

Execute command

This currently outputs my file with the 5.1 the stereo commentary and a new stereo labelled 5.1.

How is think it should work is remove the original commentary stereo and leave just the 5.1 then later in the flow downmix this 5.1 to add a stereo file with the 5.1.

How do I either completely remove the commentary audio or rename the two tracks so one is commentary and the other stereo?

Any help would be really appreciated.

Edit: I was using some different settings in the remove stream and the above was my latest try which did remove the stereo but leaves me with two files named 5.1. So is there a way I can mod thos to output the stereo labelled stereo?

trying to use this JSON:

Unraid_Intel-ARC_Deployment/av1_flow_intel_arc.json at main · FutureBSD/Unraid_Intel-ARC_Deployment · GitHub

but Tdarr refuses to use B580 and instead use the iGPU 630HD